Macula Densa snRNAseq Quality Control
Jonathan Nelson
04 April 2025
## [1] "C:/Users/jonat/OneDrive - University of Southern California/Github/macula_densa_scRNAseq"options(future.globals.maxSize = 74 * 1024^3) # 55 GB
getOption("future.globals.maxSize") #59055800320## [1] 794568949761 Load Raw Macula Densa .rds file
1.1 nFeatures, nCounts, and percent.mt
1.2 Identify clusters
1.2.1 Cluster 0: MD1
1.2.2 Cluster 1: MD2
1.2.3 Cluster 2: MD: Activated (cFos)
1.2.4 Cluster 3: EC (Pecam1)
1.2.5 Cluster 4: Stroma (Vim)
1.2.6 Cluster 5: CD (Aqp2)
1.2.7 Cluster 6: IC (Kit)
1.2.8 Cluster 7: PT (Slc34a1)
SO.markers <- FindAllMarkers(SO, only.pos = TRUE)
SO.markers %>%
group_by(cluster) %>%
dplyr::filter(avg_log2FC > 1)SO.markers %>%
group_by(cluster) %>%
dplyr::filter(avg_log2FC > 1) %>%
slice_head(n = 5) %>%
ungroup() -> top10
DoHeatmap(SO, features = top10$gene) + NoLegend()
markers.to.plot1 <- c("Lrp2", # PT
"Slc5a12", # PT-S1
"Slc13a3", # PT-S2
"Slc16a9", # PT-S3
"Havcr1", # Injured PT
"Epha7", # dTL
"Cryab", # dTL
"Cdh13", # dTL1
"Slc14a2", # dTL2
"Slc12a1", # TAL
"Umod", # TAL, DCT1
"Egf", # TAL, DCT1,
"Cldn10", # TAL
"Cldn16", # TAL
"Nos1", # MD
"Slc12a3", # DCT
"Pvalb", # DCT1
"Slc8a1", # DCT2, CNT
"Aqp2", # PC
"Slc4a1", # IC-A
"Slc26a4", # IC-B
"Nphs1", # Podo
"Ncam1", # PEC
"Flt1", # Endo
"Emcn", # Glom Endo
"Kdr", # Capillary Endo
"Pdgfrb", # Perivascular
"Pdgfra", # Fib
"Piezo2", # Mesangial
"Acta2", # Mural
"Ptprc", # Immune
"Cd74", # Macrophage
"Skap1", # B/T Cells
"Upk1b", # Uro
"Top2a" # Proliferation
)
DotPlot(SO,
features = markers.to.plot1,
dot.scale = 8,
dot.min = 0,
scale.max = 100,
scale.min = 0,
col.min = -2.5,
col.max = 2.5)+
coord_flip()
1.3 Check FeaturePlot/VlnPlot
## [1] "9230102O04Rik" "A930017K11Rik" "Apela" "Aqp2"
## [5] "Aqp3" "Calb1" "Cav1" "Defb2"
## [9] "Depdc7" "Ednrb" "Emx1" "Fxyd4"
## [13] "Gata2" "Gata3" "Iqgap2" "Kcne1"
## [17] "Mpped2" "Npnt" "Pde3b" "Pgam2"
## [21] "Phactr1" "Ptgfr" "Rhcg" "Scnn1b"
## [25] "Scnn1g" "Spink8" "St6gal1" "Stc1"
## [29] "Tbx2" "Tmem45b" "Trpv5" "Avpr2"
## [33] "Trpv4" "Tmem229a" "Atp2b2" "Ptgs1"
## [37] "Srcin1" "Slc2a9" "A4galt" "Adm"
## [41] "Kcnj10" "Cdc42ep1" "Rasd1" "Cryab"
## [45] "Sgk1" "Ccnd1" "Tacstd2" "Dab2"
## [49] "Slc8a1" "Gm44120" "Angpt1" "Tmem52b"
## [53] "Hsd11b2" "Hspg2" "Adh1" "Kcnq1"
## [57] "Smtn" "Itpkb" "Ddah1" "Itga2b"
## [61] "Cav2" "Rhbg" "Gchfr" "Csrp2"
## [65] "Hdac7" "Kitl" "Itpr2" "Plcd3"
## [69] "Rap1gap" "Phlda1" "Krt7" "Hhatl"
## [73] "Tspan1" "Slc6a6" "Cox7a1" "Rnf186"
## [77] "Gprc5b" "Ntn4" "1110019B22Rik" "St6galnac2"
## [81] "Rec8" "Grb14" "Cavin2" "Tpd52l1"
## [85] "Gm43305" "Slc12a1" "Sfrp1" "Nuak2"
## [89] "Defb1" "Igfbp7" "Sec14l1" "4930550C14Rik"
## [93] "Col27a1" "Il17re" "Irx1" "Emb"
## [97] "Lhx1" "Cldn4" "Car15" "Etnk1"
## [101] "Nudt4" "Pik3r1" "Zfand5" "Cd63"
## [105] "Zfp503" "Slc5a1" "Cox7b" "Eprn"
## [109] "Robo2" "Irx2" "Bmp3" "Mgst1"
## [113] "Abca13" "Scd2" "Slc44a3" "Cldn10"
## [117] "Aebp1" "Gm10053" "Gm42031" "Ftl1"
## [121] "Chchd10" "Ctsc" "Prdx5" "Tnfaip8"
## [125] "Gm22133" "Slc25a5" "Apoe" "Cyba"
## [129] "Uqcrb" "Itprid2" "Plcl1" "Serinc3"
## [133] "Pcolce" "L1cam" "Sptbn2" "Gm49980"
## [137] "Cox6a1" "Thbs1" "Cox6c" "Gapdh"
## [141] "Aif1l" "Pdzk1ip1" "Camk2d" "Osbpl1a"
## [145] "Cox5a" "Exph5" "Ttc36" "Pth1r"
## [149] "Pamr1" "Ndufa4" "Ramp3" "Cox5b"
## [153] "Herpud1" "Wwc2" "Ltc4s" "Esd"
## [157] "Ndufc1" "Atp5h" "Atp5o" "Sh3bgrl3"
## [161] "Enpp1" "Peli2" "Scnn1a" "Uqcrq"
## [165] "Ppp1r1a" "Atp5j2" "Col4a1" "Eno1"
## [169] "Gm47708" "Nadk2" "Pappa2" "Apoo"
## [173] "Atp5mpl" "Ndufb1-ps" "Mfge8" "Flvcr1"
## [177] "Ndufa5" "Cdk14" "Ranbp3l" "Cyb5a"
## [181] "Atp5k" "Cycs" "Ces1d" "Efhd1"
## [185] "Cnn3" "Sdc4" "Uqcr11" "H3f3b"
## [189] "Mapt" "Ctsb" "Nos1" "Cd47"
## [193] "Uqcr10" "Mt2" "Atp5g3" "Enpp2"
## [197] "Atp5md" "Rps5" "Smim4" "S100g"
## [201] "Cth" "Pacsin2" "mt-Cytb" "Atp5g1"
## [205] "Atp5j" "Mt1" "mt-Rnr1" "Avpr1a"
## [209] "Ppargc1a" "Lix1" "Atp5e" "Neat1"
## [213] "Tfrc" "Cdkn1c" "Fam241a" "Ndufa1"
## [217] "Plcb1" "Fxyd2" "Cox7a2" "mt-Rnr2"
## [221] "Cdo1" "Fzd4" "Snn" "Ndrg1"
## [225] "Fam3c" "Cacna1d" "Lgmn" "Pde10a"
## [229] "Sgms2" "Bex1" "Hes1" "Ptma"
## [233] "Tmem176b" "Col4a3" "Itga4" "Paqr5"
## [237] "Idh2" "Bex4" "Ablim1" "Aldoa"
## [241] "Napsa" "Cox8a" "Gm28437" "Car4"
## [245] "Tfap2b" "Oxct1" "Rps3" "Scarf2"
## [249] "Ndufb6" "Slit2" "Tmem176a" "Car8"
## [253] "Tshr" "Cwh43" "Ctsz" "Clic1"
## [257] "Por" "Hif1a" "Tmem221" "Ppp2r3a"
## [261] "Epcam" "Degs2" "Tspan18" "Erbb4"
## [265] "Tmem72" "Cst3" "Ahnak" "Cox7c"
## [269] "Plekha1" "Gm10108" "Ptger3" "Oat"
## [273] "Sytl2" "Asph" "Kl" "Aco2"
## [277] "Gm10221" "Shd" "Cox6b1" "Myef2"
## [281] "Tmsb10" "Ndufa3" "Hspa1b" "Tmsb4x"
## [285] "Rpl9" "Ndufa2" "Uqcrh" "Ndufa6"
## [289] "Fam53b" "Mfsd4b1" "Bcam" "Gstt1"
## [293] "Rps8" "Rps21" "Zcchc18" "Ndufv3"
## [297] "Ptges" "Sqstm1" "Pla2g7" "Lmo1"
## [301] "Uroc1" "Rpl3" "Myo10" "mt-Nd4l"
## [305] "Atp2a2" "Col18a1" "Rnf152" "Rpl7"
## [309] "Clcnkb" "Srpk2" "Smpdl3a" "Gm12337"
## [313] "Rps14" "Pantr1" "Slc31a1" "Atp5pb"
## [317] "Rassf6" "Rrbp1" "Sh2d4a" "Gstm1"
## [321] "Selenom" "Tmem59" "H2-D1" "Atp6v0b"
## [325] "S100a1" "Pkig" "Mgll" "Wwc1"
## [329] "Gm3379" "Ucp2" "Mrpl42" "Iscu"
## [333] "H2bc4" "D630024D03Rik" "Acsl4" "Idh3a"
## [337] "Pgk1" "Fth1" "Epn3" "Ndufb10"
## [341] "Atp5b" "Atp2b1" "Rps7" "Ndufa13"
## [345] "Thsd4" "Rps3a1" "Gnas" "S100a11"
## [349] "Tecr" "Bex3" "Tbck" "Rhoc"
## [353] "Hspa1a" "S100a10" "Slc24a5" "Hoxb7"
## [357] "Nrp1" "Cldn16" "Kcnk1" "mt-Nd2"
## [361] "Clint1" "Gm10925" "Rps24" "Hoxb4"
## [365] "Gm4735" "Zmiz1" "Gm9732" "Sptbn1"
## [369] "Pbx3" "Npc2" "Rps9" "Ipcef1"
## [373] "Kng2" "Srrm2" "Cnbp" "Rgs2"
## [377] "Tmem64" "Atp2b4" "Acat1" "Sox4"
## [381] "Higd1a" "Gm12338" "Rps4x" "Atp1b1"
## [385] "Glud1" "Ftl1-ps1" "Bola3" "Ccdc80"
## [389] "Emp2" "Fam174b" "Pgp" "Cyb5b"
## [393] "mt-Nd1" "Tcf4" "Bmpr1b" "Tpi1"
## [397] "Tmem158" "Stk32b" "Klhdc7a" "Fahd1"
## [401] "Bst2" "Ndufa8" "Bag1" "Zbtb20"
## [405] "Dock8" "Gga2" "B830017H08Rik" "Peg3"
## [409] "Gclc" "Uqcrfs1" "C77080" "Spp1"
## [413] "Fzd7" "Pkm" "Tagln2" "Paip2"
## [417] "Gnai1" "Ndufv2" "Metrnl" "Reep5"
## [421] "Smco4" "Usp2" "Pigp" "Dusp9"
## [425] "Nipal2" "Cdkl1" "Got1" "Rpl9-ps7"
## [429] "Fras1" "Cystm1" "Ier3" "Ndufb5"
## [433] "Tspan33" "Lurap1" "Ndufa12" "Ndufa11"
## [437] "Ndufb11" "Zfp36l1" "Dbndd2" "Map1lc3a"
## [441] "Rpl17-ps3" "Hpcal1" "Sdc2" "Wsb1"
## [445] "Muc1" "Rps16" "Stx7" "Gas5"
## [449] "Gcgr" "Mrpl36" "Nsg2" "Bcl2"
## [453] "Rpl30" "Glis2" "Baiap2" "Mcub"
## [457] "Tspan15" "Vdac1" "Rpl8" "Hoxc6"
## [461] "Tbxas1" "Sod2" "Eef1b2" "Prkd1"
## [465] "4930581F22Rik" "Akr1b8" "Dctd" "Acss1"
## [469] "Ndufaf4" "Chchd2" "Rpl18a" "Ndufb2"
## [473] "Gabarapl1" "Ndst4" "Dapk1" "Ndufc2"
## [477] "Ank3" "Tspan12" "Slc25a17" "Gm28438"
## [481] "Slc50a1" "Cox20" "Ndufb7" "Ctsl"
## [485] "Prom1" "Rnf145" "Gm15427" "Nenf"
## [489] "Pla2g4a" "Hoxc9" "B3gnt2" "Gm28661"
## [493] "Srgap1" "Mdh2" "Ppp1r14b" "Stard4"
## [497] "Atp5a1" "Ninl" "Ripor1" "BC064078"
## [501] "Rps15a" "Kank1" "Nampt" "Mrps21"
## [505] "Ppm1h" "Rpl34" "Klk1b4" "Fmc1"
## [509] "Slc3a2" "Rps15" "Vegfa" "Arhgap24"
## [513] "2300009A05Rik" "Pde4d" "Chpt1" "Gal3st1"
## [517] "Rps2" "Jun" "Lrpap1" "Pappa"
## [521] "Nr3c2" "Trim2" "mt-Nd4" "Mfsd4a"
## [525] "Ube2h" "Mgst3" "Fut8" "Ldhb"
## [529] "Micos10" "Cebpd" "Thoc2l" "St3gal4"
## [533] "Kctd1" "Plcxd3" "Lmna" "Tpt1"
## [537] "Utrn" "Hoxc8" "Rps27a" "Slc29a1"
## [541] "Naca" "B2m" "Gdf11" "Ndfip1"
## [545] "Nudt19" "Selenok" "Syne1" "Cbx5"
## [549] "Eef1d" "Ly6e" "Atp5l" "Atp6v0e"
## [553] "Tmed6" "Npm1" "Tubb2a" "Sema6a"
## [557] "Ttc14" "Hsp90ab1" "Sptlc2" "Enpp4"
## [561] "Cgnl1" "Ksr2" "Hoxb2" "Ass1"
## [565] "Rps13" "Arid5b" "Selenow" "Gm14414"
## [569] "Atp4a" "Rps10" "Aard" "Gm5526"
## [573] "Dynlt1f" "Hnrnpa0" "Sema5a" "Spcs2"
## [577] "Rpsa-ps2" "Bcl7a" "Ptgs2" "Akap13"
## [581] "Hoxb9" "Micall1" "Mettl7a1" "Snrnp70"
## [585] "Aig1" "Rps3a2" "Olfm1" "Anxa11"
## [589] "Glis3" "Ndufs5-ps" "Cdc42bpa" "Gm24447"
## [593] "Hexa" "Rpl6l" "Atp5c1" "Dbi"
## [597] "Hoxb5os" "Myh10" "Fau" "Ermp1"
## [601] "Saraf" "Etv1" "Atp6v1f" "Enox1"
## [605] "Frmd4a" "Gpc3" "Erp29" "Cdh6"
## [609] "Gm45716" "Cog7" "Fuom" "Smdt1"
## [613] "Gm6136" "Esrra" "Mcee" "Rps19"
## [617] "Cox4i1" "Ptpn3" "Slc9a3r1" "Serpinb1a"
## [621] "Rtn4" "Srrm1" "Mvb12a" "Bcl2l1"
## [625] "Rps16-ps2" "Rpl12" "Ezr" "Rpl4"
## [629] "Gm7206" "Id4" "Rps20" "Setd5"
## [633] "Klf9" "Prss23" "Tnfrsf21" "Pnisr"
## [637] "Ndufb4c" "Baiap2l2" "Shmt1" "Dynlt1a"
## [641] "Tcf24" "Tsn" "Fus" "Rabac1"
## [645] "Mal" "Ddah2" "Tle4" "Rack1"
## [649] "Ctnna1" "Hoxb6" "Rpl27a" "F11r"
## [653] "Itm2c" "Etfa" "Snw1" "Mtdh"
## [657] "Rps12" "Thap4" "Rpl10-ps3" "Gm12251"
## [661] "Plscr2" "Mtus1" "Sf3b1" "Mtfp1"
## [665] "Srpr" "Tspan7" "Gm26377" "Rps18"
## [669] "6330403K07Rik" "Tenm2" "Serpinb6a" "Gm4045"
## [673] "Defb42" "Tmed9" "Rpl10a-ps1" "Cirbp"
## [677] "Slc39a8" "Rpl5" "Eif3f" "Gm4332"
## [681] "Ddt" "Creg1" "Aimp1" "Auts2"
## [685] "Nr3c1" "Kifc3" "Diaph2" "Ndufa10"
## [689] "Rpl10" "Hnrnpa3" "Sdhc" "Jund"
## [693] "Rps27" "Pkdcc" "Gpx6" "Mcrip2"
## [697] "Rmdn3" "Cldn7" "Serpinh1" "Ddrgk1"
## [701] "Sorl1" "Gaa" "Lcorl" "Rmnd5a"
## [705] "Cpt1a" "Atp5d" "Sult1c2" "Hk1"
## [709] "Ptprf" "Tusc3" "Ssbp2" "Notch2"
## [713] "Luc7l2" "Mal2" "Trmt112" "Gm9790"
## [717] "Gm20554" "Tln2" "Mmp14" "Fam162a"
## [721] "Gm11353" "C2cd5" "Clu" "Slc25a35"
## [725] "Nop10" "Tmem116" "Ddit4l" "Srp14"
## [729] "Pdk3" "Dynll1" "Ctsh" "Ndufb8"
## [733] "Thra" "Rps23" "Gm4294" "Cldn8"
## [737] "Mdh1" "Cab39l" "Slc25a3" "Mia2"
## [741] "Kidins220" "Gm48582" "Pdgfa" "Dmxl1"
## [745] "Me3" "Atp9a" "Sema4a" "Usp50"
## [749] "Tnfaip2" "Ypel2" "Rsrp1" "Ubb"
## [753] "Rnasek" "Gm5436" "Sdcbp" "Cd9"
## [757] "Gstp-ps" "Hpn" "Riok3" "Ndufs8"
## [761] "Smc1a" "Capns1" "Tmed3" "Pigq"
## [765] "Tmem47" "Nsmce3" "Rnf128" "Minpp1"
## [769] "Slc16a7" "H2-K1" "Kdm1b" "Mrps36"
## [773] "Gm44386" "Celsr2" "U2surp" "Coa3"
## [777] "Nfix" "Ndufa12-ps" "Hadh" "Slc9a2"
## [781] "Ndufb3" "Gm2962" "Hnrnpu" "Vps13c"
## [785] "Gm15590" "Gnb4" "Rpl18-ps2" "Gm3362"
## [789] "Mtln" "Sec62" "Rpl23" "Srsf7"
## [793] "Cspp1" "Trabd2b" "Eps8" "Prrc2c"
## [797] "Ifi27" "Rpsa" "Hoxc10" "Inpp5a"
## [801] "AI838599" "Slc35g1" "Gm13436" "Bptf"
## [805] "Net1" "Aff1" "Clcn5" "Bod1l"
## [809] "Bcat2" "Rpl11" "Iah1" "Tmbim6"
## [813] "Lamp2" "Sh3bp5" "Rdm1" "4921524J17Rik"
## [817] "Dcdc2a" "Tbc1d1" "Cx3cl1" "Pdpn"
## [821] "Ncam1" "Rpl22" "Eef1g" "Rpl29"
## [825] "Prpf4b" "Mccc1" "Hnrnpdl" "Rpl15-ps2"
## [829] "Klhl3" "Cnpy2" "Kcnj16" "Cited4"
## [833] "Mif" "Adamtsl2" "Rbm39" "Gm14539"
## [837] "Sri" "Gars" "Hyi" "C1qtnf4"
## [841] "Smim24" "Syne2" "Mpp6" "Tmtc4"
## [845] "Atl2" "Cd81" "Ash1l" "Tmed4"
## [849] "Stx16" "Rpl14" "Tmem254c" "Mapk13"
## [853] "Slc25a4" "Rpl26" "Atraid" "Ncor1"
## [857] "Atp6v1a" "ccdc198" "Etfb" "Ly6a"
## [861] "Bex2" "Arl6" "Smim5" "Srsf11"
## [865] "Stk26" "Cers4" "Gm13340" "Hmgn5"
## [869] "Ghitm" "Knop1" "Hadhb" "Itgav"
## [873] "Nhs" "Tnrc6c" "Chd2" "Ing2"
## [877] "Serinc1" "Nono" "Trps1" "Csrp1"
## [881] "Dhrs4" "Extl1" "Hoxb3" "Wnt10a"
## [885] "Mme" "Tsc22d2" "Srsf3" "Gm10039"
## [889] "Hebp1" "Gm10774" "Cnot6l" "Myo18a"
## [893] "Ppp3ca" "Nudt22" "Gstk1" "Pura"
## [897] "Stk25" "Cyp2j11" "Ptk7" "Rbm3"
## [901] "Pou3f3" "Rtn3" "Pdzrn4" "Batf3"
## [905] "Gm3511" "Mtx2" "Luzp1" "Grk3"
## [909] "Fbxo44" "6430548M08Rik" "Rps19-ps2" "Hoxd3os1"
## [913] "Sash1" "Cryz" "Cdhr5" "Arhgef12"
## [917] "Prelid2" "Ethe1" "Rplp1" "Arnt2"
## [921] "Itgb1" "Vkorc1" "Rpl10a" "Ckap4"
## [925] "Camk2n1" "4632427E13Rik" "Ppm1j" "Gas6"
## [929] "Hnrnpd" "Rpl19" "Hnrnph1" "Gm29216"
## [933] "Acin1" "Dld" "Tmem141" "Timp3"
## [937] "Ssr4" "Pfkp" "Rpl17" "Uhrf2"
## [941] "Nipsnap1" "Rps6-ps1" "Gls" "Ppfibp1"
## [945] "Dhcr24" "Gpm6b" "Ddost" "Csnk1a1"
## [949] "Dop1b" "Ldha" "Rpl18" "Rnpep"
## [953] "Acss3" "Sdhd" "Tubb5" "Fgf9"
## [957] "Zfp326" "Hnrnpk" "Eef1a1" "Nsd1"
## [961] "Rps26" "Vash2" "Itpr1" "Micos13"
## [965] "Tpp1" "Prnp" "Kng1" "Nsmce4a"
## [969] "Cers6" "Eif1" "Atp6ap1" "Nrip1"
## [973] "Stim2" "Hint2" "Smarca2" "Mafg"
## [977] "Sema3c" "Bhlhe40" "Nhsl2" "Abca3"
## [981] "Rock1" "Sv2a" "Ctsf" "Ptprd"
## [985] "Srsf5" "Uqcrc2" "Tmem50a" "Nedd4l"
## [989] "Rpn2" "Myo1b" "Ndufs5" "Cabcoco1"
## [993] "Psmd4" "Dusp14" "Ube2d3" "Clta"
## [997] "Tmem254b" "Rabgef1" "Trim47" "Plin3"
## [1001] "Ccdc141" "Tnrc6a" "Nr2f2" "Atf7ip"
## [1005] "F2rl1" "Eva1a" "Lmo7" "Emc7"
## [1009] "Mfsd4b3-ps" "Rbm47" "Ran" "Trp53i13"
## [1013] "Mmd" "Fnbp1l" "Txnip" "Matr3"
## [1017] "Gabarap" "Gm9349" "Rps27l" "Vps37d"
## [1021] "Sgms1" "Rpl37" "Birc2" "Cables1"
## [1025] "Luzp2" "Ywhah" "Srsf1" "Glmp"
## [1029] "Rdx" "Wdr72" "Ppdpf" "Trim35"
## [1033] "Iqgap1" "Trim44" "Dnah12" "Sfn"
## [1037] "Tmem238" "Hipk2" "Tgoln1" "Gm28911"
## [1041] "H2az2" "Laptm4b" "Gigyf2" "Atrx"
## [1045] "Mindy2" "Dbt" "Msi2" "Cmc2"
## [1049] "Trim7" "Crim1" "Tle1" "Umod"
## [1053] "Pdia3" "Mgat4a" "Cetn3" "Cldnd1"
## [1057] "Hmgb2" "Rchy1" "Pde1a" "Gcnt2"
## [1061] "Morf4l1" "Dhrs7" "Ptprj" "Rpl23a"
## [1065] "Prkar1a" "Fads1" "Os9" "Canx"
## [1069] "Car12" "Gm8971" "Atp11a" "Gnb2"
## [1073] "Rpl37a" "Ccnt2" "Rsrc2" "Ergic3"
## [1077] "Rplp0" "Gm7536" "Mxd4" "Hivep2"
## [1081] "Slc2a1" "Klk1b5" "Rps8-ps1" "Rab20"
## [1085] "Rbm25" "Fam107b" "Anxa5" "Rpl7a"
## [1089] "Tle5" "Osbpl6" "Selenop" "Ndufb4"
## [1093] "Hoxd11" "Ptbp3" "Cdc42se2" "Psip1"
## [1097] "Gm9843" "Gpi1" "Aamp" "Pla2g12a"
## [1101] "Acot9" "Hint3" "Zfp950" "Bicc1"
## [1105] "Jarid2" "Srebf2" "Sms" "Pdha1"
## [1109] "Snx2" "Slc1a3" "Vgll4" "Fh1"
## [1113] "Map1lc3b" "Apmap" "Prxl2a" "Vdac2"
## [1117] "1110008P14Rik" "Nktr" "Rpl32" "Lmbrd1"
## [1121] "Rsu1" "Atp6v1g1" "Gm2830" "Gm13226"
## [1125] "Hnrnpa2b1" "Limch1" "Prrc2b" "Gm45847"
## [1129] "Pls3" "Tm2d1" "Itga1" "Wdfy3"
## [1133] "Aifm1" "Grina" "Gm46209" "Slc25a12"
## [1137] "Tm7sf3" "Psmb1" "Atp6v1c2" "Jak1"
## [1141] "Slc7a4" "Morn2" "Nfic" "Gpx4-ps2"
## [1145] "Glo1" "Malat1" "Cyp39a1" "Efcab14"
## [1149] "Kmt2a" "Psme1" "Kdsr" "Dpysl2"
## [1153] "Tax1bp1" "Ndufs1" "Dlat" "Ints6l"
## [1157] "2610528J11Rik" "Ccdc107" "Tia1" "Sfpq"
## [1161] "Myh9" "Pabpc1" "Ogfrl1" "Ik"
## [1165] "Clk1" "Sgpp1" "Uqcrc1" "Purb"
## [1169] "Tmed1" "Mettl26" "Rex1bd" "Gstm2"
## [1173] "Lrp6" "Ptprg" "Zranb2" "Mafb"
## [1177] "Ormdl3" "Slc15a2" "Rps27rt" "Akap9"
## [1181] "Ndufab1" "Hnrnpl" "Dock1" "Ano6"
## [1185] "Megf9" "Gna11" "Dab2ip" "Dtymk"
## [1189] "Grcc10" "Rpgrip1" "Gm8451" "Rpl28"
## [1193] "Crebbp" "Dpyd" "Acot1" "Sgcb"
## [1197] "Acadsb" "Gsk3b" "Lamp1" "Rpl13-ps3"
## [1201] "Cttnbp2" "Serbp1" "Txndc5" "Dgat2"
## [1205] "Frk" "Eif6" "Dip2c" "Vav3"
## [1209] "Fbxo6" "Rnf187" "Cyfip2" "Cryl1"
## [1213] "Eif5a" "Ythdc1" "Tmbim1" "Ube2a"
## [1217] "Pi4ka" "Orai1" "Calr" "Ip6k2"
## [1221] "Raly" "Magi2" "Map3k3" "Syt11"
## [1225] "Klf13" "Eif3i" "Higd2a" "Abhd6"
## [1229] "Arhgef18" "Ddx50" "Ywhaq" "Id3"
## [1233] "Ptpn18" "Elob" "Tmpo" "Pnrc1"
## [1237] "Btf3" "Efemp1" "Shfl" "Bclaf1"
## [1241] "Eif3k" "Cebpb" "Rora" "Ube2b"
## [1245] "Ldhb-ps" "Tbrg1" "Sypl" "Tmx1"
## [1249] "Gm9616" "Col4a3bp" "Macroh2a1" "Olfm4"
## [1253] "Ctsa" "Ppp1r2" "Leng8" "Luc7l3"
## [1257] "Wee1" "Nucb1" "Dync1h1" "Pdlim5"
## [1261] "Ralbp1" "Pgrmc1" "Kmt2e" "Gm11914"
## [1265] "Cox17" "Eif3h" "Ndufs4" "Slc16a11"
## [1269] "Sfxn1" "Acsl3" "Erg28" "Cachd1"
## [1273] "Tmem222" "Csad" "Wasl" "Oard1"
## [1277] "Sec11c" "C1qtnf12" "Gnptg" "Sgpl1"
## [1281] "Lpar6" "Mrpl57" "Vegfb" "Itgb5"
## [1285] "Mecom" "Pold4" "Prdx4" "Gstm5"
## [1289] "Fndc3a" "Slc16a10" "Gprasp1" "Tma7"
## [1293] "Wfdc2" "Spcs1" "Ktn1" "Dcps"
## [1297] "Letm2" "Lman1" "Thrap3" "Coq7"
## [1301] "Pten" "Maged1" "Rpl14-ps1" "Krcc1"
## [1305] "Slco4a1" "Crebzf" "Selenbp1" "Cebpa"
## [1309] "Kif5b" "Ppa2" "Trim24" "Arhgef28"
## [1313] "Xiap" "Slirp" "Nifk" "Acadm"
## [1317] "Degs1" "Phf3" "Cmtm8" "Rab11fip2"
## [1321] "Ndufs3" "Tardbp" "Psma7" "Crem"
## [1325] "Erbb3" "Rsbn1" "Yipf1" "Rps23-ps1"
## [1329] "Gm10177" "Gng5" "Zfp467" "Sec31a"
## [1333] "Asah1" "Hoxa9" "Irf2bp2" "Exosc3"
## [1337] "Rbbp6" "Gm8355" "Bnip3" "Oaz1"
## [1341] "Fermt2" "Fuca1" "Pafah1b3" "Gm11539"
## [1345] "Mecp2" "Spag9" "Eif4a2" "Arid4b"
## [1349] "Snhg20" "Cox5b-ps" "Tceal8" "Cd151"
## [1353] "Mrpl12" "Pdia6" "Ahcyl2" "Sorbs2"
## [1357] "Rpl22l1" "Yif1a" "Casr" "Sdf2"
## [1361] "Nedd4" "Pmepa1" "Eri3" "Dlgap4"
## [1365] "Vps25" "Serinc2" "Bag4" "Tmem9"
## [1369] "Sbds" "Pfn2" "Hivep1" "Rbpms"
## [1373] "Mycbp2" "H2aj" "Hspe1" "Timp2"
## [1377] "Dusp23" "Pcdhgc4" "Marf1" "Hnrnph3"
## [1381] "Maml3" "Hspa8" "Thoc1" "Rbmx"
## [1385] "Cox7a2l" "Usp22" "Zfp266" "Sec61g"
## [1389] "Csde1" "R3hdm2" "Rxrb" "Nucks1"
## [1393] "Mrpl51" "Mydgf" "Dtnbp1" "Cdc25b"
## [1397] "Gcc2" "Pabpn1" "Cnot4" "Gm15459"
## [1401] "Smg6" "Calm1" "Adam15" "Rbm5"
## [1405] "Atxn1" "Slc38a10" "Mef2a" "Pbx1"
## [1409] "Cyc1" "Pygl" "Smim6" "Dctn3"
## [1413] "Coq9" "Pitpna" "Snrpb" "Csf2ra"
## [1417] "Anp32e" "Sucla2" "Hnf1b" "Gm8430"
## [1421] "Rcbtb2" "Pnn" "Dnajc3" "Ttc3"
## [1425] "Top1" "Rnd3" "Plpp2" "Fam204a"
## [1429] "Rpl6" "Cs" "Gadd45g" "Pdhb"
## [1433] "Psmd7" "Frg1" "Casp6" "Nptn"
## [1437] "Chd3" "Myo6" "Atp6v0a4" "Nme3"
## [1441] "Actr10" "4932438A13Rik" "Nol7" "Macf1"
## [1445] "Rprd2" "Hibadh" "Gng12" "Oip5os1"
## [1449] "Rpl13" "Ccni" "Ptpra" "Egf"
## [1453] "Ddx24" "Abhd2" "Sgta" "Rpl13a"
## [1457] "Tufm" "Gm10232" "Rell1" "Ache"
## [1461] "Las1l" "Kif16b" "Scin" "Btbd3"
## [1465] "Brd2" "Ggh" "Dbnl" "Lsm4"
## [1469] "Mkln1" "Zadh2" "Izumo4" "Tm9sf2"
## [1473] "Tmem191c" "Immt" "Zfr" "Nsun7"
## [1477] "Pink1" "Sestd1" "Usp24" "Plet1"
## [1481] "Arhgdia" "Tcf7l2" "Tspan3" "Lamb1"
## [1485] "Rpl36a-ps3" "Prdx3" "Nipbl" "Rictor"
## [1489] "Arpc1a" "Sf3b5" "Arfgef3" "Ndfip2"
## [1493] "Cpsf6" "Hoxb8" "Fam174a" "Zfp644"
## [1497] "Spopl" "Rtl8a" "Mfsd1" "Kcnq1ot1"
## [1501] "Hsd17b12" "Slc25a39" "Plekhj1" "Ddo"
## [1505] "Ccs" "Sumo3" "Derl1" "Plau"
## [1509] "Arhgap5" "Tpr" "Ap2b1" "Nfkbia"
## [1513] "1110004F10Rik" "Fbxl17" "Slc7a8" "Sun1"
## [1517] "Slc35a1" "2900052L18Rik" "Napa" "Dcaf17"
## [1521] "Eif3a" "Cstb" "Hnmt" "Mlh3"
## [1525] "Abr" "Tmem234" "Prxl2b" "Kif21a"
## [1529] "Smarce1" "Gnpda1" "Anapc5" "Mettl27"
## [1533] "Ppm1a" "Sh3yl1" "Jade1" "Fabp3"
## [1537] "Hnrnpc" "Met" "Stox2" "Pak1ip1"
## [1541] "Ptk2" "Itfg2" "Rpl36a" "Mgat4b"
## [1545] "Ep300" "Txn2" "Taldo1" "Ptprk"
## [1549] "Ildr1" "Osbpl9" "Cmpk1" "Klf6"
## [1553] "Cyb5r3" "Mxi1" "Nemf" "Mymx"
## [1557] "Pde4dip" "Ptov1" "Babam2" "Camta1"
## [1561] "Foxn3" "Retreg2" "Gcsh" "Igf2r"
## [1565] "Setd7" "Dtx3" "Spc25" "Psmd11"
## [1569] "Ppm1g" "Pcyt2" "Inpp5j" "Anapc16"
## [1573] "Zfp612" "Ddx17" "Ranbp2" "Sf3b2"
## [1577] "Pdcd4" "Isoc1" "Adam10" "P4hb"
## [1581] "M6pr" "Nop53" "Papss1" "Fkbp4"
## [1585] "Pam" "Echs1" "Slc48a1" "Romo1"
## [1589] "Mrpl34" "Zbtb38" "Commd4" "Zfp871"
## [1593] "Swt1" "Ttc39b" "Imp3" "Akap11"
## [1597] "Perp" "Egln2" "Pet100" "Agtrap"
## [1601] "Ankrd11" "Hagh" "Stag2" "Zfp638"
## [1605] "Slc44a4" "Fam98c" "Npdc1" "Trappc6b"
## [1609] "Surf1" "AI480526" "Eif3m" "Fubp1"
## [1613] "Cetn2" "Tulp4" "Arl4a" "Pcm1"
## [1617] "Hsbp1" "Zfp445" "Ate1" "Glrx5"
## [1621] "Unc50" "Pole4" "Huwe1" "Cr1l"
## [1625] "Prps2" "Ubr2" "Dpm1" "Ogt"
## [1629] "Rtf1" "Car2" "Clk4" "Clybl"
## [1633] "Tmem106b" "Mrpl20" "Ninj1" "Myl12b"
## [1637] "Ogfod3" "Slc5a3" "Myl12a" "Eny2"
## [1641] "Crip2" "Mif-ps" "Larp1b" "Sgpp2"
## [1645] "H4c4" "Hdgfl3" "Wls" "Ubn2"
## [1649] "Manbal" "Selenoh" "Naxd" "Xbp1"
## [1653] "Usp40" "Tasor" "Mif4gd" "Mapre2"
## [1657] "Ring1" "Arl6ip5" "Atad2b" "Dnajb6"
## [1661] "2410006H16Rik" "Mfap1b" "Map7" "Tmod3"
## [1665] "Dnlz" "Mri1" "Pfkl" "Scn4b"
## [1669] "Zmynd11" "Ppia" "Yy1" "Bpgm"
## [1673] "Ccdc47" "Clptm1" "Phldb2" "Phf20l1"
## [1677] "Dctn4" "Phf14" "Tomm5" "Supt4a"
## [1681] "Rcn2" "Dhx36" "Cbx6" "Bcas2"
## [1685] "Smc3" "Caprin1" "Mysm1" "Polr2e"
## [1689] "Slc39a1" "1810026B05Rik" "Tsc22d1" "Arpc4"
## [1693] "Slc25a30" "Hspb1" "Ebp" "Amfr"
## [1697] "Chchd3" "Mrps15" "Rps28" "Aplp2"
## [1701] "Blnk" "Rbm42" "Gdi1" "Bod1"
## [1705] "Smchd1" "Hook3" "Rpl24" "Pld3"
## [1709] "Wbp2" "Cyhr1" "Hoxb5" "Ensa"
## [1713] "Lzts2" "Smad7" "Gipc2" "Rab11b"
## [1717] "Igf1r" "Snrnp48" "Rps23-ps2" "Gstt3"
## [1721] "Eprs" "Hnrnpr" "Gm38394" "Tuba1b"
## [1725] "Dnajc10" "Pim3" "Abhd16a" "9530068E07Rik"
## [1729] "Spr" "Dusp11" "Tsc22d3" "Mphosph8"
## [1733] "Dsp" "Use1" "Hist1h2al" "Itga6"
## [1737] "Txndc15" "Pkp4" "Ndufb9" "Smarca5"
## [1741] "Wnk4" "Gm24270" "Esf1" "Cenpb"
## [1745] "Phip" "Pbrm1" "Ndrg2" "Mesd"
## [1749] "Cdkn1b" "Zc3h13" "Mir6236" "Gpx4"
## [1753] "Ndufs2" "Azin1" "Septin7" "CT010467.1"
## [1757] "Gm37376" "Ier2" "Fkbp11" "Nme7"
## [1761] "Lars2" "Gm23935" "Trpm7" "Tspan8"
## [1765] "Atp6v0d1" "Actb" "Klk1" "Wfdc15b"
## [1769] "Wnk1"### Cluster 2: MD: Activated (cFos)
### Cluster 3:
### Cluster 4: EC (Pecam1)
### Cluster 5: CD (Aqp2)
### Cluster 6: IC (Kit)
### Cluster 7: PT (Slc34a1)
FeaturePlot(SO, "Nos1")
2 Filter non-MD Cells and re-cluster
SO2 <- SCTransform(SO2) %>%
RunPCA() %>%
FindNeighbors(dims = 1:30) %>%
FindClusters() %>%
RunUMAP(dims = 1:30)## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## | | | 0% | |== | 2% | |=== | 4% | |===== | 7% | |====== | 9% | |======== | 11% | |========= | 13% | |=========== | 15% | |============ | 17% | |============== | 20% | |=============== | 22% | |================= | 24% | |================== | 26% | |==================== | 28% | |===================== | 30% | |======================= | 33% | |======================== | 35% | |========================== | 37% | |=========================== | 39% | |============================= | 41% | |============================== | 43% | |================================ | 46% | |================================= | 48% | |=================================== | 50% | |===================================== | 52% | |====================================== | 54% | |======================================== | 57% | |========================================= | 59% | |=========================================== | 61% | |============================================ | 63% | |============================================== | 65% | |=============================================== | 67% | |================================================= | 70% | |================================================== | 72% | |==================================================== | 74% | |===================================================== | 76% | |======================================================= | 78% | |======================================================== | 80% | |========================================================== | 83% | |=========================================================== | 85% | |============================================================= | 87% | |============================================================== | 89% | |================================================================ | 91% | |================================================================= | 93% | |=================================================================== | 96% | |==================================================================== | 98% | |======================================================================| 100%## | | | 0% | |== | 2% | |=== | 4% | |===== | 7% | |====== | 9% | |======== | 11% | |========= | 13% | |=========== | 15% | |============ | 17% | |============== | 20% | |=============== | 22% | |================= | 24% | |================== | 26% | |==================== | 28% | |===================== | 30% | |======================= | 33% | |======================== | 35% | |========================== | 37% | |=========================== | 39% | |============================= | 41% | |============================== | 43% | |================================ | 46% | |================================= | 48% | |=================================== | 50% | |===================================== | 52% | |====================================== | 54% | |======================================== | 57% | |========================================= | 59% | |=========================================== | 61% | |============================================ | 63% | |============================================== | 65% | |=============================================== | 67% | |================================================= | 70% | |================================================== | 72% | |==================================================== | 74% | |===================================================== | 76% | |======================================================= | 78% | |======================================================== | 80% | |========================================================== | 83% | |=========================================================== | 85% | |============================================================= | 87% | |============================================================== | 89% | |================================================================ | 91% | |================================================================= | 93% | |=================================================================== | 96% | |==================================================================== | 98% | |======================================================================| 100%## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
##
## Number of nodes: 11529
## Number of edges: 391221
##
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.7901
## Number of communities: 15
## Elapsed time: 1 seconds
markers.to.plot2 <- c("Lrp2", # PT
"Slc5a12", # PT-S1
"Slc13a3", # PT-S2
"Slc16a9", # PT-S3
"Havcr1", # Injured PT
"Epha7", # dTL
"Cryab", # dTL
"Cdh13", # dTL1
"Slc14a2", # dTL2
"Slc12a1", # TAL
"Umod", # TAL, DCT1
"Egf", # TAL, DCT1,
"Cldn10", # TAL
"Cldn16", # TAL
"Nos1", # MD
"Slc12a3", # DCT
"Pvalb", # DCT1
"Slc8a1", # DCT2, CNT
"Aqp2", # PC
"Slc4a1", # IC-A
"Slc26a4", # IC-B
"Nphs1", # Podo
"Ncam1", # PEC
"Flt1", # Endo
"Emcn", # Glom Endo
"Kdr", # Capillary Endo
"Pdgfrb", # Perivascular
"Pdgfra", # Fib
"Piezo2", # Mesangial
"Acta2", # Mural
"Ptprc", # Immune
"Cd74", # Macrophage
"Skap1", # B/T Cells
"Upk1b", # Uro
"Top2a", # Proliferation
"Cldn5",
"Jun",
"Fosb"
)
DotPlot(SO2,
features = markers.to.plot2,
dot.scale = 8,
dot.min = 0,
scale.max = 100,
scale.min = 0,
col.min = -2.5,
col.max = 2.5)+
coord_flip()
3 Subset and recluster
SO3 <- SCTransform(SO3) %>%
RunPCA() %>%
FindNeighbors(dims = 1:10) %>%
FindClusters(resolution = .3) %>%
RunUMAP(dims = 1:10)## | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100%## | | | 0% | |== | 2% | |=== | 4% | |===== | 7% | |====== | 9% | |======== | 11% | |========= | 13% | |=========== | 15% | |============ | 17% | |============== | 20% | |=============== | 22% | |================= | 24% | |================== | 26% | |==================== | 28% | |===================== | 30% | |======================= | 33% | |======================== | 35% | |========================== | 37% | |=========================== | 39% | |============================= | 41% | |============================== | 43% | |================================ | 46% | |================================= | 48% | |=================================== | 50% | |===================================== | 52% | |====================================== | 54% | |======================================== | 57% | |========================================= | 59% | |=========================================== | 61% | |============================================ | 63% | |============================================== | 65% | |=============================================== | 67% | |================================================= | 70% | |================================================== | 72% | |==================================================== | 74% | |===================================================== | 76% | |======================================================= | 78% | |======================================================== | 80% | |========================================================== | 83% | |=========================================================== | 85% | |============================================================= | 87% | |============================================================== | 89% | |================================================================ | 91% | |================================================================= | 93% | |=================================================================== | 96% | |==================================================================== | 98% | |======================================================================| 100%## | | | 0% | |== | 2% | |=== | 4% | |===== | 7% | |====== | 9% | |======== | 11% | |========= | 13% | |=========== | 15% | |============ | 17% | |============== | 20% | |=============== | 22% | |================= | 24% | |================== | 26% | |==================== | 28% | |===================== | 30% | |======================= | 33% | |======================== | 35% | |========================== | 37% | |=========================== | 39% | |============================= | 41% | |============================== | 43% | |================================ | 46% | |================================= | 48% | |=================================== | 50% | |===================================== | 52% | |====================================== | 54% | |======================================== | 57% | |========================================= | 59% | |=========================================== | 61% | |============================================ | 63% | |============================================== | 65% | |=============================================== | 67% | |================================================= | 70% | |================================================== | 72% | |==================================================== | 74% | |===================================================== | 76% | |======================================================= | 78% | |======================================================== | 80% | |========================================================== | 83% | |=========================================================== | 85% | |============================================================= | 87% | |============================================================== | 89% | |================================================================ | 91% | |================================================================= | 93% | |=================================================================== | 96% | |==================================================================== | 98% | |======================================================================| 100%## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
##
## Number of nodes: 11458
## Number of edges: 350779
##
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.8595
## Number of communities: 5
## Elapsed time: 1 seconds
SO.markers <- FindAllMarkers(SO3, only.pos = TRUE)
SO.markers %>%
group_by(cluster) %>%
dplyr::filter(avg_log2FC > .5) %>%
slice_head(n = 10) %>%
ungroup() -> top10
DoHeatmap(SO3, features = top10$gene) + NoLegend()
4 Session Info
## R version 4.4.3 (2025-02-28 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 22631)
##
## Matrix products: default
##
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## time zone: America/Los_Angeles
## tzcode source: internal
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] CellChat_2.1.2 igraph_2.1.4
## [3] ggtext_0.1.2 ComplexHeatmap_2.22.0
## [5] UpSetR_1.4.0 EnhancedVolcano_1.24.0
## [7] lubridate_1.9.4 forcats_1.0.0
## [9] purrr_1.0.4 readr_2.1.5
## [11] tidyr_1.3.1 tidyverse_2.0.0
## [13] enrichplot_1.26.6 clusterProfiler_4.14.6
## [15] gplots_3.2.0 kableExtra_1.4.0
## [17] ggvenn_0.1.10 data.table_1.17.0
## [19] readxl_1.4.5 openxlsx_4.2.8
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## [23] stringr_1.5.1 here_1.0.1
## [25] DESeq2_1.46.0 SummarizedExperiment_1.36.0
## [27] Biobase_2.66.0 MatrixGenerics_1.18.1
## [29] matrixStats_1.5.0 GenomicRanges_1.58.0
## [31] GenomeInfoDb_1.42.3 IRanges_2.40.1
## [33] S4Vectors_0.44.0 BiocGenerics_0.52.0
## [35] ggrepel_0.9.6 RColorBrewer_1.1-3
## [37] ggpmisc_0.6.1 ggpp_0.5.8-1
## [39] tibble_3.2.1 BiocManager_1.30.25
## [41] ggplot2_3.5.1 knitr_1.50
## [43] patchwork_1.3.0 SeuratObject_5.0.2
## [45] Seurat_4.4.0 dplyr_1.1.4
##
## loaded via a namespace (and not attached):
## [1] R.methodsS3_1.8.2 goftest_1.2-3 Biostrings_2.74.1
## [4] vctrs_0.6.5 ggtangle_0.0.6 spatstat.random_3.3-2
## [7] digest_0.6.37 png_0.1-8 shape_1.4.6.1
## [10] registry_0.5-1 deldir_2.0-4 parallelly_1.42.0
## [13] MASS_7.3-64 reshape2_1.4.4 httpuv_1.6.15
## [16] foreach_1.5.2 qvalue_2.38.0 withr_3.0.2
## [19] ggrastr_1.0.2 xfun_0.51 ggfun_0.1.8
## [22] ggpubr_0.6.0 survival_3.8-3 memoise_2.0.1
## [25] ggbeeswarm_0.7.2 MatrixModels_0.5-3 gson_0.1.0
## [28] systemfonts_1.2.1 tidytree_0.4.6 zoo_1.8-13
## [31] GlobalOptions_0.1.2 gtools_3.9.5 pbapply_1.7-2
## [34] R.oo_1.27.0 Formula_1.2-5 KEGGREST_1.46.0
## [37] promises_1.3.2 httr_1.4.7 rstatix_0.7.2
## [40] globals_0.16.3 fitdistrplus_1.2-2 rstudioapi_0.17.1
## [43] UCSC.utils_1.2.0 miniUI_0.1.1.1 generics_0.1.3
## [46] DOSE_4.0.0 ggalluvial_0.12.5 zlibbioc_1.52.0
## [49] polyclip_1.10-7 GenomeInfoDbData_1.2.13 SparseArray_1.6.2
## [52] xtable_1.8-4 doParallel_1.0.17 evaluate_1.0.3
## [55] S4Arrays_1.6.0 hms_1.1.3 irlba_2.3.5.1
## [58] colorspace_2.1-1 polynom_1.4-1 ggnetwork_0.5.13
## [61] ROCR_1.0-11 reticulate_1.41.0.1 spatstat.data_3.1-6
## [64] magrittr_2.0.3 lmtest_0.9-40 later_1.4.1
## [67] ggtree_3.14.0 lattice_0.22-6 spatstat.geom_3.3-5
## [70] NMF_0.28 future.apply_1.11.3 SparseM_1.84-2
## [73] scattermore_1.2 cowplot_1.1.3 RcppAnnoy_0.0.22
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## [79] sna_2.8 gridBase_0.4-7 caTools_1.18.3
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## [88] abind_1.4-8 gridGraphics_0.5-1 locfit_1.5-9.12
## [91] sp_2.2-0 bit_4.6.0 fastmatch_1.1-6
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## [97] plotly_4.10.4 mime_0.12 splines_4.4.3
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## [124] ica_1.0-3 broom_1.0.7 sass_0.4.9
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## [130] RANN_2.6.2 farver_2.1.2 yaml_2.3.10
## [133] cli_3.6.4 leiden_0.4.3.1 lifecycle_1.0.4
## [136] uwot_0.2.3 backports_1.5.0 BiocParallel_1.40.0
## [139] timechange_0.3.0 gtable_0.3.6 rjson_0.2.23
## [142] ggridges_0.5.6 progressr_0.15.1 parallel_4.4.3
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## [148] bit64_4.6.0-1 Rtsne_0.17 yulab.utils_0.2.0
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## [163] glue_1.8.0 spam_2.11-1 XVector_0.46.0
## [166] rprojroot_2.0.4 treeio_1.30.0 gridExtra_2.3
## [169] R6_2.6.1 labeling_0.4.3 cluster_2.1.8
## [172] rngtools_1.5.2 aplot_0.2.5 statnet.common_4.11.0
## [175] vipor_0.4.7 DelayedArray_0.32.0 tidyselect_1.2.1
## [178] xml2_1.3.8 AnnotationDbi_1.68.0 future_1.34.0
## [181] munsell_0.5.1 KernSmooth_2.23-26 htmlwidgets_1.6.4
## [184] fgsea_1.32.2 rlang_1.1.5 spatstat.sparse_3.1-0
## [187] spatstat.explore_3.3-4 beeswarm_0.4.0